RCPシナリオに基づく英国の電力・ガス需要予測：MLを用いたネットゼロエネルギー安全保障のための分析

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a novel integrated framework for joint electricity and gas demand forecasting under climate and transition scenarios, useful for energy systems modeling.

🏢実務担当者:Offers insights for capacity and storage planning, electrification strategies, and gas network investment decisions under climate and net-zero pathways.

🏛政策担当者:Highlights the need to incorporate climate-sensitive demand projections into energy security and net-zero planning, with implications for infrastructure investment.

Climate change is altering energy-demand patterns through changing temperatures and heating and cooling requirements. Long-term energy-demand projections are essential for energy security, infrastructure planning, and preparing net-zero energy systems. However, integrated assessments of climate-sensitive electricity and gas demand trajectories in the UK under long-term climate-forcing pathways and net-zero transition assumptions remains limited. To address this gap, this study develops a scenario-based machine-learning framework to jointly project electricity and gas demand in the UK up to 2050 under climate-forcing pathways. CMIP6 daily temperature projections at 0.25° resolution are used to calculate Heating Degree Days and Cooling Degree Days under low-, intermediate-, and high-forcing pathways, labelled RCP2.6, RCP4.5, and RCP8.5. These indicators are used as inputs to Random Forest models for electricity and gas demand. By 2050, electricity demand under RCP8.5 is 4.1% higher than under RCP2.6, while gas demand is 6.8% lower. Under the net-zero adjustment, gas demand declines because of the assumed 75% reduction in gas use, while electricity demand rises as part of displaced gas demand shifts to electricity. Adjusted electricity demand differs by 2–3 TWh between the highest- and lowest-warming pathways, while adjusted gas demand differs by 7–8 TWh. The framework jointly assesses climate-sensitive electricity and gas demand and links these projections to net-zero gas-reduction and electrification assumptions. The results support electricity-capacity and storage planning, electrification strategies, hydrogen infrastructure investment, and decisions on the future role of gas networks in UK energy-security planning under changing climate and transition conditions across Britain.

• semanticscholar https://doi.org/10.3390/en19163830first seen 2026-08-20 05:05:41 · last seen 2026-09-22 04:56:38
• openalex https://doi.org/10.3390/en19163830first seen 2026-09-06 05:03:06